This document discusses using an artificial neural network (ANN) approach to develop an intelligent energy management control system for a hybrid vehicle to improve fuel consumption. It first reviews different existing control strategies for hybrid vehicles, including rule-based and optimal control strategies. It then discusses various ANN models that have been developed and applied to hybrid vehicles, including using Elman neural networks and recurrent neural networks for control and modeling. The document proposes developing separate ANN models for the vehicle, driver behavior, environment, and roadway and integrating them into an overall architecture to analyze the vehicle's performance under different conditions and optimize the energy management system.
This document discusses a proposed fuzzy logic-based control strategy for a parallel hybrid vehicle. The control strategy aims to interpret the driver's command and optimize fuel consumption and emissions by efficiently splitting power between the internal combustion engine and electric motor. A fuzzy logic controller is proposed that takes the driver command and state of charge as inputs to determine how to meet the driver's torque demand while achieving satisfactory fuel efficiency and emissions. The proposed strategy and hybrid vehicle configuration are described.
This document discusses developing an optimal control strategy for managing the energy usage in plug-in hybrid electric vehicles (PHEVs). It proposes formulating an optimal control problem and solving it using Pontryagin's minimum principle to determine the control policy. The strategy aims to minimize fuel consumption while allowing the battery to be depleted during vehicle operation. The strategy is evaluated using a simulation of a PHEV model that was developed and validated at The Ohio State University.
1) The document discusses speed control of a universal motor using two controllers - an output rate controller and an output reset controller. Ant colony optimization is used to tune the parameters of the controllers.
2) Mathematical models of the universal motor are developed. Simulation results show that the proposed ant colony optimization technique tunes the controllers' parameters optimally, improving their performance for speed control of the motor under varying load conditions.
3) The tuning results in zero overshoot and undershoot, slight rise and settling times, and a fast response for the motor speed when subjected to different load disturbances.
IRJET- Particle Swarm Intelligence based Dynamics Economic Dispatch with Dail...IRJET Journal
This document discusses particle swarm intelligence techniques for solving economic load dispatch problems. It begins with an abstract that introduces economic load dispatch as a technique for allocating power generation levels among generating units to minimize costs while meeting demand and operational constraints. It then provides background on economic load dispatch and describes how particle swarm optimization can be applied to solve non-convex economic dispatch problems. Finally, it reviews several related works applying evolutionary algorithms like particle swarm optimization, genetic algorithms, and cuckoo search to economic load dispatch problems.
Design of a Monitoring-combined Siting Scheme for Electric Vehicle Chargers IJECEIAES
This paper designs a siting scheme for public electric vehicle chargers based on a genetic algorithm working on charger monitoring streams. The monitoring-combined allocation scheme runs on a long-term basis, iterating the process of collecting data, analyzing demand, and selecting candidates. The analysis of spatio-temporal archives, acquired from the fast chargers currently in operation, focuses on the per-charger hot hour and proximity effect to justify demand balancing in geographic cluster level. It leads to the definition of a fitness function representing the standard deviation of percharger load and cluster-by-cluster distribution. In a chromosome, each binary integer is associated with a candidate and its static fields include the index to the cluster to which it is belonging. The performance result obtained from a prototype implementation reveals that the proposed scheme can stably distribute the charging load with an addition of a new charger, achieving the reduction of standard deviation from 8.7 % to 4.7 % in the real-world scenario.
life cycle cost analysis of a solar energy based hybrid power systemINFOGAIN PUBLICATION
The importance of life-cycle cost analysis of an integrated solar power system is explained in this paper. To analyze the energy power and cash flow computations, there exist many commercial types of energy audit softwares like Emat, Optimizer, Homer, Energy gauge, Treat and so on. Among the aforementioned audit softwares, homer software is selected since it consists of several built-in options to perform audit studies. Homer software basically utilizes the concept of finding the total net present cost to represent the life-cycle cost of the total system. This software is vividly used for obtaining the optimized energy audit solutions to integrate several equipments embedding into a single workable system.
Study and Analysis of Nonlinear Constrained Components A Study of Plug-in Hyb...ijtsrd
Today transportation is one of the rapidly evolving technologies in the world. With the stringent mandatory emission regulations and high fuel prices, researchers and manufacturers are ever increasingly pushed to the frontiers of research in pursuit of alternative propulsion systems. Electrically propelled vehicles are one of the most promising solutions among all the other alternatives, as far as reliability, availability, feasibility and safety issues are concerned. However, the shortcomings of a fully electric vehicle in fulfilling all performance requirements make the electrification of the conventional engine powered vehicles in the form of a plug-in hybrid electric vehicle PHEV the most feasible propulsion systems. Sadia Andaleeb "Study and Analysis of Nonlinear Constrained Components (A Study of Plug-in Hybrid Electric Vehicle)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd20308.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/20308/study-and-analysis-of-nonlinear-constrained-components-a-study-of-plug-in-hybrid-electric-vehicle/sadia-andaleeb
This document discusses a proposed fuzzy logic-based control strategy for a parallel hybrid vehicle. The control strategy aims to interpret the driver's command and optimize fuel consumption and emissions by efficiently splitting power between the internal combustion engine and electric motor. A fuzzy logic controller is proposed that takes the driver command and state of charge as inputs to determine how to meet the driver's torque demand while achieving satisfactory fuel efficiency and emissions. The proposed strategy and hybrid vehicle configuration are described.
This document discusses developing an optimal control strategy for managing the energy usage in plug-in hybrid electric vehicles (PHEVs). It proposes formulating an optimal control problem and solving it using Pontryagin's minimum principle to determine the control policy. The strategy aims to minimize fuel consumption while allowing the battery to be depleted during vehicle operation. The strategy is evaluated using a simulation of a PHEV model that was developed and validated at The Ohio State University.
1) The document discusses speed control of a universal motor using two controllers - an output rate controller and an output reset controller. Ant colony optimization is used to tune the parameters of the controllers.
2) Mathematical models of the universal motor are developed. Simulation results show that the proposed ant colony optimization technique tunes the controllers' parameters optimally, improving their performance for speed control of the motor under varying load conditions.
3) The tuning results in zero overshoot and undershoot, slight rise and settling times, and a fast response for the motor speed when subjected to different load disturbances.
IRJET- Particle Swarm Intelligence based Dynamics Economic Dispatch with Dail...IRJET Journal
This document discusses particle swarm intelligence techniques for solving economic load dispatch problems. It begins with an abstract that introduces economic load dispatch as a technique for allocating power generation levels among generating units to minimize costs while meeting demand and operational constraints. It then provides background on economic load dispatch and describes how particle swarm optimization can be applied to solve non-convex economic dispatch problems. Finally, it reviews several related works applying evolutionary algorithms like particle swarm optimization, genetic algorithms, and cuckoo search to economic load dispatch problems.
Design of a Monitoring-combined Siting Scheme for Electric Vehicle Chargers IJECEIAES
This paper designs a siting scheme for public electric vehicle chargers based on a genetic algorithm working on charger monitoring streams. The monitoring-combined allocation scheme runs on a long-term basis, iterating the process of collecting data, analyzing demand, and selecting candidates. The analysis of spatio-temporal archives, acquired from the fast chargers currently in operation, focuses on the per-charger hot hour and proximity effect to justify demand balancing in geographic cluster level. It leads to the definition of a fitness function representing the standard deviation of percharger load and cluster-by-cluster distribution. In a chromosome, each binary integer is associated with a candidate and its static fields include the index to the cluster to which it is belonging. The performance result obtained from a prototype implementation reveals that the proposed scheme can stably distribute the charging load with an addition of a new charger, achieving the reduction of standard deviation from 8.7 % to 4.7 % in the real-world scenario.
life cycle cost analysis of a solar energy based hybrid power systemINFOGAIN PUBLICATION
The importance of life-cycle cost analysis of an integrated solar power system is explained in this paper. To analyze the energy power and cash flow computations, there exist many commercial types of energy audit softwares like Emat, Optimizer, Homer, Energy gauge, Treat and so on. Among the aforementioned audit softwares, homer software is selected since it consists of several built-in options to perform audit studies. Homer software basically utilizes the concept of finding the total net present cost to represent the life-cycle cost of the total system. This software is vividly used for obtaining the optimized energy audit solutions to integrate several equipments embedding into a single workable system.
Study and Analysis of Nonlinear Constrained Components A Study of Plug-in Hyb...ijtsrd
Today transportation is one of the rapidly evolving technologies in the world. With the stringent mandatory emission regulations and high fuel prices, researchers and manufacturers are ever increasingly pushed to the frontiers of research in pursuit of alternative propulsion systems. Electrically propelled vehicles are one of the most promising solutions among all the other alternatives, as far as reliability, availability, feasibility and safety issues are concerned. However, the shortcomings of a fully electric vehicle in fulfilling all performance requirements make the electrification of the conventional engine powered vehicles in the form of a plug-in hybrid electric vehicle PHEV the most feasible propulsion systems. Sadia Andaleeb "Study and Analysis of Nonlinear Constrained Components (A Study of Plug-in Hybrid Electric Vehicle)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd20308.pdf
Paper URL: https://www.ijtsrd.com/engineering/mechanical-engineering/20308/study-and-analysis-of-nonlinear-constrained-components-a-study-of-plug-in-hybrid-electric-vehicle/sadia-andaleeb
Active power and cost allocation in open access environment utilizing power f...ecij
This document summarizes a research paper that proposes a new method for allocating transmission usage costs and losses among generators and loads in an open access electricity market. It considers contingency conditions by introducing the Maximum Line Outage Distribution Factor (MLODF), which depends on power redistribution after an outage. The proposed method uses power flow tracing based on a modified Kirchhoff matrix to determine each user's contribution to line flows and losses. Transmission costs are then allocated using the MW-Mile method based on these determined contributions under both normal and contingency conditions. The reliability and accuracy of the proposed MLODF-based cost allocation method is tested on a sample 6-bus power system.
There are various types of research in each academic area. Systematic research should be explored and studied in order to extend the development of knowledge. In this report an engineering topic is selected that focuses on hybrid electric motorbikes. Comparing and analysing two relevant journal papers which is divided into several parts in this report. Firstly, an introduction presents the background, and a literature review is conducted to identify the expectation. Secondly, the report carries out the aim and objectives that are approached through the well-structured methods and methodology. Finally, analysing the collected data and the conclusion contribute to part of report as well. The interpretation of hybrid electric motorbike is discovered so as to assist the further proposal.
Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in...TELKOMNIKA JOURNAL
Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made.
Hybrid vehicle drivetrains- My published manuscript in International Research...ZelieusNamirian
This document provides an overview of hybrid vehicle drivetrains. It begins by defining key terms like powertrain, drive train, and Energy Management Systems (EMS). It then describes the main hybrid vehicle power train system topologies: series, parallel, and power-split hybrids. For each topology, it outlines the basic configuration and operation. The document focuses on outlining the characteristics of different hybridization types and identifying areas for potential research developments in hybrid vehicle drivetrains and EMS optimization.
Design of spark ignition engine speed control using bat algorithm IJECEIAES
This document summarizes a research paper that proposes using the bat algorithm to design a speed controller for a spark ignition engine. The paper first provides background on spark ignition engines, PI controllers, and the bat algorithm. It then describes using the bat algorithm to optimize the proportional and integral gains of a PI controller for a simulated spark ignition engine model in MATLAB/SIMULINK. The objective function is to minimize the integrated time absolute error of the engine speed response. Simulation results under different speed variations and load conditions are presented and analyzed to demonstrate that the bat algorithm can enhance engine speed performance compared to a conventional PI controller.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a research paper on simulating a fuzzy-based power system stabilizer. It describes defining the structure of the fuzzy inference system with two inputs (load and compensator) and one output (change in kW). It then discusses defining membership functions and degrees for the input/output variables. Next, it explains constructing rules by combining input variables. Lastly, it analyzes the system's performance by viewing the rule interactions graphically and in 3D.
Economical and Reliable Expansion Alternative of Composite Power System under...IJECEIAES
The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions.
The field of power systems operation and control including renewable energy (RE) along with power, quality is considered as one of the major technical challenges among the researchers and practicing engineers. Several types of renewable energy resources are available on earth such as solar, wind, Geo-thermal, hydro, etc. The foremost resources of renewable energy are - Sunlight and Wind. The wind energy is always a center of attraction for power engineers. In the wind energy system, the pitch angle of turbine blades is playing an important role in controlling the power output of the system. The pitch angle imposes two types of control on the wind turbine system: aerodynamic torque and the rotational velocity of the turbine system. These parameters directly affect the performance of the wind power generation system in terms of the profile of power, voltage, and current. Conventionally, PID control-based system modeling has been used to evaluate the optimal pitch angle for a given wind pattern. However, PID based Pitch Angle Identification require regular tuning against variation in wind velocity and significant large time for tuning. Thus, Artificial Intelligence could provide a better solution in comparison to PID Based tuning strategy. The present work shows the evaluation of the optimal pitch angle of the wind turbines for variable wind velocity using the Fuzzy Logic Control Strategy. The test results are obtained by MATLAB Simulink modeling of the wind power generation system. The simulation shows that fuzzy logic control will provide an optimal pitch angle to obtain more efficient solutions. The existing fuzzy control-based simulation model solutions can be utilized as a testbed for evaluating the optimal pitch Angle of any geographical region. In the present work, the optimal pitch angle of Various Geographical regions of India.
Design of automatic navigation control system for agricultural vehicleeSAT Journals
The document describes research on designing an automatic navigation control system for agricultural vehicles. A hardware platform was built using an ARM chip, RTK-GPS positioning system, and angle sensor. A hydraulic control valve test platform was developed to test and select valves. A navigation valve block was created and tested on a model vehicle to realize electrical control of steering. Navigation control algorithms were studied, including a pure pursuit path tracking model. Experiments showed the system could stably track a straight path in real-time, meeting precision agriculture requirements.
This document provides a review of fuzzy microscopic traffic models. It begins with an introduction describing the importance of traffic models and limitations of existing microscopic models. It then outlines the aim, objectives, and justification of integrating fuzzy logic into microscopic traffic models. Key aspects summarized include a review of existing microscopic car-following models and their limitations, an overview of fuzzy logic and how it can describe driver behavior more realistically, and directions for future research.
IRJET- Comparison of GA and PSO Optimization Techniques to Optimal Planning o...IRJET Journal
This document presents a comparison of genetic algorithm (GA) and particle swarm optimization (PSO) techniques for optimally placing electric vehicle charging stations in a local distribution system. It describes using GA and PSO in MATLAB simulations to determine charging station locations that minimize real and reactive power losses. The results found that PSO requires fewer iterations and less time to achieve optimal solutions compared to GA, though GA may find solutions with slightly lower losses. Overall, both techniques provide effective methods for optimizing charging station placement to support electric vehicles.
Optimal Placement of FACTS Controllers for Congestion Management in the Dereg...IJECEIAES
This paper proposes a methodology to determine the optimal location of Flexible AC Transmission System (FACTS) controllers for Congestion Management (CM) in the restructured electrical power system. An approach to find the optimum placement of Thyristor Controlled Phase Angle Regulators (TCPAR) and Thyristor Controlled Series Compensators (TCSC) has been proposed in this paper. The proposed methodology is based on the sensitivity of transmission loss which a controller is installed. The total system losses and the power flows are considered as the performance indices. The traditional optimal power flow (OPF) problem is modified to include the market players, who will compete and trade simultaneously, ensuring the system operation stays within the security limits. In this paper, pool and bilateral contracts are considered. Here, an integrated methodology is proposed that includes the FACTS Controllers in a bilateral contract framework to maintain the system security and to minimize the deviations from the contractual requirements. The simulation results on IEEE 30 bus system show that the sensitivity factors could be used effectively for the optimal location of FACTS controllers in response to the required objectives.
This document summarizes a research paper that investigates improving the dynamic responses of grid-connected permanent magnet synchronous generator (PMSG) wind turbines using a fuzzy logic controller (FLC). The paper proposes using an FLC to control the pitch angle of the turbine blades based on wind speed and active power inputs. This allows for faster response compared to prior methods, leading to smoother power output and preventing mechanical damage. The system is modeled and simulated in Matlab/Simulink. Results show the FLC approach effectively regulates turbine output power under varying wind speeds and load conditions.
Allocation of Transmission Cost Using Power Flow Tracing MethodsIJERA Editor
In the open access restructured power system market, it is necessary to develop an appropriate pricing scheme that can provide the useful economic information to market participants, such as generation, transmission companies and customers. Though many methods have already been proposed, but accurately estimating and allocating the transmission cost in the transmission pricing scheme is still a challenging task. This work addresses the problem of allocating the cost of the transmission network to generators and demands. In this work four methods using DC Power flow and AC power flow have been attempted. They are MW-Mile Method, MVA-Mile Method, GGDF method and Bialek Tracing method.MVA-Mile method and Bialek Tracing method applies AC power flow and considers apparent power flows. The purpose of the present work is to allocate the cost pertaining to the transmission lines of the network to all the generators and demands. A load flow solution is run and, the proposed method determines how line flows depend on nodal currents. This result is then used to allocate network costs to generators and demands. The technique presented in this work is related to the allocation of the cost to GENCO‘s TRANSCO‘s and DISCO‘s. A technique for tracing the flow of electricity of lines among generators with GGDF and Bialek upstream looking algorithm is proposed. With these methods correct economic signals are generated for all players. All these methods are tested on IEEE 14 bus system.
This document provides a detailed review of vibration energy harvesting in automotive suspension systems. It discusses how regenerative suspensions with energy harvesting shock absorbers can convert wasted vibration energy into electricity. The most common energy harvesting systems used in vehicle suspensions are electromagnetic harvesters, which can be either linear or rotary. Linear electromagnetic harvesters directly convert vertical vibration into electricity, while rotary harvesters use mechanisms like ball screws or rack-pinions to transform linear vibration into rotational motion to drive a generator. Both types aim to improve fuel efficiency by recovering energy normally lost as heat in traditional dampers.
This paper reviews load forecasting using a neuro-fuzzy system. It discusses how neural networks and fuzzy logic can be combined in a neuro-fuzzy system to improve load forecasting accuracy. The paper first provides background on load forecasting and different techniques used. It then proposes using a neuro-fuzzy approach where load data is classified with fuzzy sets and a neural network is trained on each classification to forecast loads. Combining the learning ability of neural networks with the symbolic reasoning of fuzzy logic in a neuro-fuzzy system can potentially provide more accurate short-term load forecasts. The paper concludes that neuro-fuzzy systems show advantages over other statistical and AI methods for load forecasting.
This document describes a project to optimize the fuel consumption of a series electric hybrid vehicle over the New European Driving Cycle (NEDC) using different control strategies. A team of 4 master's students worked on various subsystems of the vehicle including the electrical machine, power electronics, battery, generator, internal combustion engine (ICE), and supervisor controller. The team developed Simulink models of each subsystem and integrated them to simulate different operating strategies over the NEDC cycle with the goal of minimizing fuel consumption. Key results showed how the state of charge and fuel consumption varied over the cycle depending on the initial and minimum SOC levels used in the control strategy.
The document describes a new efficient shower water heater design that uses a novel heat transfer method. Key points:
- The design aims to significantly reduce power consumption compared to conventional electric water heaters by heating water in small volumes directly in the shower head rather than a large reservoir.
- Coiled heating elements housed in small tubes are placed inside the shower head openings so that only a few milliliters of water pass through and are heated at a time.
- This micro heating approach is expected to exponentially reduce the power needed compared to traditional systems that heat larger volumes of water at once.
- Other benefits may include lower hazards, portability, lighter weight, and enabling the use of small renewable power
This document compares communication links between optical fiber and VSAT for offshore platforms. It discusses that optical fiber provides higher speeds, better signal quality, and higher reliability than VSAT, but has higher upfront costs. VSAT can cover larger distances at a lower cost, but has lower speeds and quality. For clusters of platforms near shore, fiber is often preferable due to its performance, but for wide coverage VSAT may be more cost effective despite its limitations. The key factors in choosing a link include cost, capacity, reliability, backup options, and services required.
Active power and cost allocation in open access environment utilizing power f...ecij
This document summarizes a research paper that proposes a new method for allocating transmission usage costs and losses among generators and loads in an open access electricity market. It considers contingency conditions by introducing the Maximum Line Outage Distribution Factor (MLODF), which depends on power redistribution after an outage. The proposed method uses power flow tracing based on a modified Kirchhoff matrix to determine each user's contribution to line flows and losses. Transmission costs are then allocated using the MW-Mile method based on these determined contributions under both normal and contingency conditions. The reliability and accuracy of the proposed MLODF-based cost allocation method is tested on a sample 6-bus power system.
There are various types of research in each academic area. Systematic research should be explored and studied in order to extend the development of knowledge. In this report an engineering topic is selected that focuses on hybrid electric motorbikes. Comparing and analysing two relevant journal papers which is divided into several parts in this report. Firstly, an introduction presents the background, and a literature review is conducted to identify the expectation. Secondly, the report carries out the aim and objectives that are approached through the well-structured methods and methodology. Finally, analysing the collected data and the conclusion contribute to part of report as well. The interpretation of hybrid electric motorbike is discovered so as to assist the further proposal.
Nowadays, the location and sizing of distributed generation (DG) units in power system network are crucial to be at optimal as it will affect the power system operation in terms of stability and security. In this paper, a new technique termed as Immune Log-Normal Evolutionary Programming (ILNEP) is applied to find the optimal location and size of distributed generation units in power system network. Voltage stability is considered in solving this problem. The proposed technique has been tested on the IEEE 26 bus Reliability Test System to find the optimal location and size of distributed generation in transmission network. In order to study the performance of ILNEP technique in solving DG Installation problem, the results produced by ILNEP were compared with other meta-heuristic techniques like evolutionary programming (EP) and artificial immune system (AIS). It is found that the proposed technique gives better solution in term of lower total system loss compared to the other two techniques.
Optimal Placement of D-STATCOM Using Hybrid Genetic and Ant Colony Algorithm ...IJAPEJOURNAL
In this work, a modern algorithm by hybrid genetic algorithm and ant colony algorithm is designed to placement and then simulated to determine the amount of reactive power by D-STATCOM. Also this method will be able to minimize the power system losses that contain power loss in transmission lines. Furthermore, in this design a IEEE 30-bus model depicted and three D-STATCOM are located in this system according to Economic Considerations. The optimal placement of each D-STATCOM is computed by the ant colony algorithm. In order to optimize placement for each D-STATCOM, two groups of ant are selected, which respectively located in near nest and far from the nest. Moreover, for every output simulation of D-STATCOM that is used to produce or absorb of reactive power, a genetic algorithm to minimizing the total network losses is applied. Finally, the result of this simulation shows net losses reduction about 150% that it verifies the new algorithm performance.
HSO: A Hybrid Swarm Optimization Algorithm for Reducing Energy Consumption in...TELKOMNIKA JOURNAL
Mobile Cloud Computing (MCC) is an emerging technology for the improvement of mobile service quality. MCC resources are dynamically allocated to the users who pay for the resources based on their needs. The drawback of this process is that it is prone to failure and demands a high energy input. Resource providers mainly focus on resource performance and utilization with more consideration on the constraints of service level agreement (SLA). Resource performance can be achieved through virtualization techniques which facilitates the sharing of resource providers’ information between different virtual machines. To address these issues, this study sets forth a novel algorithm (HSO) that optimized energy efficiency resource management in the cloud; the process of the proposed method involves the use of the developed cost and runtime-effective model to create a minimum energy configuration of the cloud compute nodes while guaranteeing the maintenance of all minimum performances. The cost functions will cover energy, performance and reliability concerns. With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). The simulation studies also showed a reduction in the number of required calculations by about 20% by the inclusion of the presented algorithms compared to the traditional static approach. There was also a decrease in the node loss which allowed the optimization algorithm to achieve a minimal overhead on cloud compute resources while still saving energy significantly. Conclusively, an energy-aware optimization model which describes the required system constraints was presented in this study, and a further proposal for techniques to determine the best overall solution was also made.
Hybrid vehicle drivetrains- My published manuscript in International Research...ZelieusNamirian
This document provides an overview of hybrid vehicle drivetrains. It begins by defining key terms like powertrain, drive train, and Energy Management Systems (EMS). It then describes the main hybrid vehicle power train system topologies: series, parallel, and power-split hybrids. For each topology, it outlines the basic configuration and operation. The document focuses on outlining the characteristics of different hybridization types and identifying areas for potential research developments in hybrid vehicle drivetrains and EMS optimization.
Design of spark ignition engine speed control using bat algorithm IJECEIAES
This document summarizes a research paper that proposes using the bat algorithm to design a speed controller for a spark ignition engine. The paper first provides background on spark ignition engines, PI controllers, and the bat algorithm. It then describes using the bat algorithm to optimize the proportional and integral gains of a PI controller for a simulated spark ignition engine model in MATLAB/SIMULINK. The objective function is to minimize the integrated time absolute error of the engine speed response. Simulation results under different speed variations and load conditions are presented and analyzed to demonstrate that the bat algorithm can enhance engine speed performance compared to a conventional PI controller.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
This document summarizes a research paper on simulating a fuzzy-based power system stabilizer. It describes defining the structure of the fuzzy inference system with two inputs (load and compensator) and one output (change in kW). It then discusses defining membership functions and degrees for the input/output variables. Next, it explains constructing rules by combining input variables. Lastly, it analyzes the system's performance by viewing the rule interactions graphically and in 3D.
Economical and Reliable Expansion Alternative of Composite Power System under...IJECEIAES
The paper intends to select the most economical and reliable expansion alternative of a composite power system to meet the expected future load growth. In order to reduce time computational quantity, a heuristic algorithm is adopted for composite power system reliability evaluation is proposed. The proposed algorithm is based on Monte-Carlo simulation method. The reliability indices are estimated for system base case and for the case of adding peaking generation units. The least cost reserve margin for the addition of five 20MW generating units sequentially is determined. Using the proposed algorithm an increment comparison approach used to illustrate the effect of the added units on the interruption and on the annual net gain costs. A flow chart introduced to explain the basic methodology to have an adequate assessment of a power system using Monte Carlo Simulation. The IEEE RTS (24-bus, 38-line) and The Jordanian Electrical Power System (46bus and 92-line) were examined to illustrate how to make decisions in power system planning and expansions.
The field of power systems operation and control including renewable energy (RE) along with power, quality is considered as one of the major technical challenges among the researchers and practicing engineers. Several types of renewable energy resources are available on earth such as solar, wind, Geo-thermal, hydro, etc. The foremost resources of renewable energy are - Sunlight and Wind. The wind energy is always a center of attraction for power engineers. In the wind energy system, the pitch angle of turbine blades is playing an important role in controlling the power output of the system. The pitch angle imposes two types of control on the wind turbine system: aerodynamic torque and the rotational velocity of the turbine system. These parameters directly affect the performance of the wind power generation system in terms of the profile of power, voltage, and current. Conventionally, PID control-based system modeling has been used to evaluate the optimal pitch angle for a given wind pattern. However, PID based Pitch Angle Identification require regular tuning against variation in wind velocity and significant large time for tuning. Thus, Artificial Intelligence could provide a better solution in comparison to PID Based tuning strategy. The present work shows the evaluation of the optimal pitch angle of the wind turbines for variable wind velocity using the Fuzzy Logic Control Strategy. The test results are obtained by MATLAB Simulink modeling of the wind power generation system. The simulation shows that fuzzy logic control will provide an optimal pitch angle to obtain more efficient solutions. The existing fuzzy control-based simulation model solutions can be utilized as a testbed for evaluating the optimal pitch Angle of any geographical region. In the present work, the optimal pitch angle of Various Geographical regions of India.
Design of automatic navigation control system for agricultural vehicleeSAT Journals
The document describes research on designing an automatic navigation control system for agricultural vehicles. A hardware platform was built using an ARM chip, RTK-GPS positioning system, and angle sensor. A hydraulic control valve test platform was developed to test and select valves. A navigation valve block was created and tested on a model vehicle to realize electrical control of steering. Navigation control algorithms were studied, including a pure pursuit path tracking model. Experiments showed the system could stably track a straight path in real-time, meeting precision agriculture requirements.
This document provides a review of fuzzy microscopic traffic models. It begins with an introduction describing the importance of traffic models and limitations of existing microscopic models. It then outlines the aim, objectives, and justification of integrating fuzzy logic into microscopic traffic models. Key aspects summarized include a review of existing microscopic car-following models and their limitations, an overview of fuzzy logic and how it can describe driver behavior more realistically, and directions for future research.
IRJET- Comparison of GA and PSO Optimization Techniques to Optimal Planning o...IRJET Journal
This document presents a comparison of genetic algorithm (GA) and particle swarm optimization (PSO) techniques for optimally placing electric vehicle charging stations in a local distribution system. It describes using GA and PSO in MATLAB simulations to determine charging station locations that minimize real and reactive power losses. The results found that PSO requires fewer iterations and less time to achieve optimal solutions compared to GA, though GA may find solutions with slightly lower losses. Overall, both techniques provide effective methods for optimizing charging station placement to support electric vehicles.
Optimal Placement of FACTS Controllers for Congestion Management in the Dereg...IJECEIAES
This paper proposes a methodology to determine the optimal location of Flexible AC Transmission System (FACTS) controllers for Congestion Management (CM) in the restructured electrical power system. An approach to find the optimum placement of Thyristor Controlled Phase Angle Regulators (TCPAR) and Thyristor Controlled Series Compensators (TCSC) has been proposed in this paper. The proposed methodology is based on the sensitivity of transmission loss which a controller is installed. The total system losses and the power flows are considered as the performance indices. The traditional optimal power flow (OPF) problem is modified to include the market players, who will compete and trade simultaneously, ensuring the system operation stays within the security limits. In this paper, pool and bilateral contracts are considered. Here, an integrated methodology is proposed that includes the FACTS Controllers in a bilateral contract framework to maintain the system security and to minimize the deviations from the contractual requirements. The simulation results on IEEE 30 bus system show that the sensitivity factors could be used effectively for the optimal location of FACTS controllers in response to the required objectives.
This document summarizes a research paper that investigates improving the dynamic responses of grid-connected permanent magnet synchronous generator (PMSG) wind turbines using a fuzzy logic controller (FLC). The paper proposes using an FLC to control the pitch angle of the turbine blades based on wind speed and active power inputs. This allows for faster response compared to prior methods, leading to smoother power output and preventing mechanical damage. The system is modeled and simulated in Matlab/Simulink. Results show the FLC approach effectively regulates turbine output power under varying wind speeds and load conditions.
Allocation of Transmission Cost Using Power Flow Tracing MethodsIJERA Editor
In the open access restructured power system market, it is necessary to develop an appropriate pricing scheme that can provide the useful economic information to market participants, such as generation, transmission companies and customers. Though many methods have already been proposed, but accurately estimating and allocating the transmission cost in the transmission pricing scheme is still a challenging task. This work addresses the problem of allocating the cost of the transmission network to generators and demands. In this work four methods using DC Power flow and AC power flow have been attempted. They are MW-Mile Method, MVA-Mile Method, GGDF method and Bialek Tracing method.MVA-Mile method and Bialek Tracing method applies AC power flow and considers apparent power flows. The purpose of the present work is to allocate the cost pertaining to the transmission lines of the network to all the generators and demands. A load flow solution is run and, the proposed method determines how line flows depend on nodal currents. This result is then used to allocate network costs to generators and demands. The technique presented in this work is related to the allocation of the cost to GENCO‘s TRANSCO‘s and DISCO‘s. A technique for tracing the flow of electricity of lines among generators with GGDF and Bialek upstream looking algorithm is proposed. With these methods correct economic signals are generated for all players. All these methods are tested on IEEE 14 bus system.
This document provides a detailed review of vibration energy harvesting in automotive suspension systems. It discusses how regenerative suspensions with energy harvesting shock absorbers can convert wasted vibration energy into electricity. The most common energy harvesting systems used in vehicle suspensions are electromagnetic harvesters, which can be either linear or rotary. Linear electromagnetic harvesters directly convert vertical vibration into electricity, while rotary harvesters use mechanisms like ball screws or rack-pinions to transform linear vibration into rotational motion to drive a generator. Both types aim to improve fuel efficiency by recovering energy normally lost as heat in traditional dampers.
This paper reviews load forecasting using a neuro-fuzzy system. It discusses how neural networks and fuzzy logic can be combined in a neuro-fuzzy system to improve load forecasting accuracy. The paper first provides background on load forecasting and different techniques used. It then proposes using a neuro-fuzzy approach where load data is classified with fuzzy sets and a neural network is trained on each classification to forecast loads. Combining the learning ability of neural networks with the symbolic reasoning of fuzzy logic in a neuro-fuzzy system can potentially provide more accurate short-term load forecasts. The paper concludes that neuro-fuzzy systems show advantages over other statistical and AI methods for load forecasting.
This document describes a project to optimize the fuel consumption of a series electric hybrid vehicle over the New European Driving Cycle (NEDC) using different control strategies. A team of 4 master's students worked on various subsystems of the vehicle including the electrical machine, power electronics, battery, generator, internal combustion engine (ICE), and supervisor controller. The team developed Simulink models of each subsystem and integrated them to simulate different operating strategies over the NEDC cycle with the goal of minimizing fuel consumption. Key results showed how the state of charge and fuel consumption varied over the cycle depending on the initial and minimum SOC levels used in the control strategy.
The document describes a new efficient shower water heater design that uses a novel heat transfer method. Key points:
- The design aims to significantly reduce power consumption compared to conventional electric water heaters by heating water in small volumes directly in the shower head rather than a large reservoir.
- Coiled heating elements housed in small tubes are placed inside the shower head openings so that only a few milliliters of water pass through and are heated at a time.
- This micro heating approach is expected to exponentially reduce the power needed compared to traditional systems that heat larger volumes of water at once.
- Other benefits may include lower hazards, portability, lighter weight, and enabling the use of small renewable power
This document compares communication links between optical fiber and VSAT for offshore platforms. It discusses that optical fiber provides higher speeds, better signal quality, and higher reliability than VSAT, but has higher upfront costs. VSAT can cover larger distances at a lower cost, but has lower speeds and quality. For clusters of platforms near shore, fiber is often preferable due to its performance, but for wide coverage VSAT may be more cost effective despite its limitations. The key factors in choosing a link include cost, capacity, reliability, backup options, and services required.
Analysis of Interfacial Microsstructure of Post Weld Heat Treated Dissimilar ...IOSR Journals
This document analyzes the interfacial microstructure of a post weld heat treated dissimilar metal weld between type 316LN austenitic stainless steel and C-steel. Single V-groove butt joints were welded using Inconel 182 welding consumables. The joints were post weld heat treated at temperatures between 898K to 973K for 1 hour. Microstructural analysis found that in the as-welded condition, the weld/C-steel interface consisted mostly of martensite or ferrite and carbides. Post weld heat treatment resulted in the precipitation of carbides at the interface. Heat treating at 973K led to recrystallized grains in the C-
This document discusses line-by-line embedded transmission pricing methodologies. It introduces concepts of deregulating the electric power industry and defines wheeling as transmitting electricity from a seller to buyer through a third party transmission network. It discusses different wheeling cost computation methodologies, including embedded and incremental cost approaches. It focuses on explaining the "line-by-line" embedded methodology in detail and how it can be used to calculate wheeling costs by allocating all existing and new transmission system costs to wheeling customers.
This document summarizes a research paper that proposes a modified channel shortener filter (MCSF) to improve the spectral efficiency of OFDM systems. The MCSF exploits the null space of an underdetermined system of equations to provide multiple independent equivalent channels to the receiver. It is shown that the MCSF can achieve a higher spectral efficiency than conventional OFDM when the cyclic prefix length is significantly smaller than the channel delay spread. Simulation results demonstrate that the MCSF improves bit error rate performance and can provide up to 2dB gain compared to full cyclic prefix OFDM systems. The MCSF has the potential to reduce receiver complexity compared to existing channel shortening approaches.
The document presents closed-form expressions for determining the bending moments in two directions of a rectangular two-way slab under a concentrated load uniformly distributed over a defined area. Equations (16) and (17) provide the bending moment expressions for the short and long directions, respectively, as functions of the span ratio, load area dimensions ratios, and other geometric properties. Comparisons are made between results from the proposed analysis method, Egyptian code approximate method, Pigweed's theory, and finite element analysis, showing better accuracy of the proposed method and Pigweed's theory over the Egyptian code method.
This document summarizes an adaptive traffic control system based on an embedded Linux board and image processing. The system uses a Raspberry Pi single board computer and OpenCV to process video frames from a digital camera mounted at an intersection. Vehicle counts on each road are determined using background subtraction and a Kalman filter algorithm. Based on the vehicle densities, different signal times are assigned to each road to improve traffic flow. The system also prioritizes emergency vehicles using GSM and GPS modules. Traffic data is stored on a web server to synchronize signals across intersections. The system aims to provide smoother traffic flow compared to fixed-time traffic signals.
Advancing Statistical Education using Technology and Mobile DevicesIOSR Journals
This document summarizes a study that explored using technology and mobile devices to advance statistical education. The study aimed to evaluate the impact of mobile technology on statistical education and analyze student adoption of mobile technology for learning statistics. It hypothesized that using mobile technology would increase student interest in statistics and that students would be inclined to adopt mobile technology for advanced statistics learning. The study examined how factors like technology acceptance, attitudes towards statistics, user satisfaction, and understanding of statistics concepts related to using an online statistics textbook on computers and iPods.
This document describes the design and implementation of an embedded control system for orienting a radar antenna. The system uses a field programmable gate array (FPGA) to process input from a radar's plane position indicator (PPI) display and control a stepper motor that adjusts the antenna's azimuth position. When a transmitter signal appears as a blip on the PPI, the FPGA commands the stepper motor to rotate clockwise or counterclockwise as needed to align the antenna to the geographic north. The FPGA was programmed using VHDL code to precisely control the stepper motor and achieve antenna orientation within 0.18 degrees. Experimental results showed the system successfully oriented the antenna based on dummy target blips
IOSR Journal of Humanities and Social Science is an International Journal edited by International Organization of Scientific Research (IOSR).The Journal provides a common forum where all aspects of humanities and social sciences are presented. IOSR-JHSS publishes original papers, review papers, conceptual framework, analytical and simulation models, case studies, empirical research, technical notes etc.
Securing Group Communication in Partially Distributed SystemsIOSR Journals
This document summarizes an approach for securing group communication in partially distributed systems. The approach divides groups into regions, each with their own Key Distribution Center (KDC). Intra-region communication uses public-key cryptography, while inter-region communication uses a hierarchical key exchange approach involving symmetric keys. Key graphs are used to represent the partial distribution structure, and rekeying strategies are employed when users join or leave groups to dynamically update keys and prevent unauthorized access. The approach aims to provide security properties like authenticity, confidentiality and integrity, while maintaining scalability for distributed systems with changing group membership.
Multiple Equilibria and Chemical Distribution of Some Bio Metals With β-Amide...IOSR Journals
Abstract: Solution Chemistry of some bivalent metal ions (viz. CoII , NiII ,CuII ,ZnII ) with β-amide α-aminosuccinate (Asparagine)/ α-aminoisoverate( Valine ) (A) and 5-methyl 2,4- dioxopyrimidine ( Thymine ) (B)ligands have been analyzed. Formation constant of quaternary metal complexes and complexation equilibria at 30±1ºC and at constant ionic strength (I=0.1M NaNO3 ) have been explored potentiometrically. Formation of quaternary species in addition to hydroxyl, protonated, binary and ternary species have been reported. Overall formation constant have been evaluated using SCOGS computer program.Species distribution curves of complexes have been plotted as a function of pH to visualize the equlibria system and was refined using ORIGIN program.The metal ligand formation constant of MA,MB,MAB and M1M2AB type of complexes follow Irving William order. The order of stability constants of quaternary systems have been observed as: Cu – Ni > Cu –Zn > Cu–Co > Ni – Zn > Ni – Co > Co –Zn. Solution structures of metal complexes with said ligands have been compared and discussed.
Magnetic Femtotesla Inductor Coil Sensor for ELF Noise Signals-( 0.1Hz to3.0 Hz)IOSR Journals
This document describes the design of a magnetic field sensor to detect extremely low frequency (ELF) noise signals between 0.1 Hz to 3 Hz. It discusses the design of the loop antenna, transformer, and amplifier components. The antenna design aims to achieve optimal sensitivity while balancing factors like size, weight and resistance. A transformer is used to electrically isolate the antenna and match its impedance to the amplifier. Design considerations are provided to achieve a flat frequency response between the transformer's lower and upper cutoff frequencies. The overall system sensitivity depends on the transformer turn ratio and balancing the amplifier's voltage and current noise sources.
This document proposes a novel algorithm to automatically segment overlapped and touching human chromosome images. The algorithm first obtains chromosome contours and calculates a discrete curvature function to identify concave points. Possible separation lines are then plotted by connecting concave points. Segmentation is performed by splitting the overlapped regions along these lines. The algorithm was able to successfully segment overlapped and touching chromosomes without human intervention.
Distributed Path Computation Using DIV AlgorithmIOSR Journals
This document summarizes research on distributed path computation algorithms that aim to prevent routing loops. It introduces the Distributed Path Computation with Intermediate Variables (DIV) algorithm, which can operate with any routing algorithm to guarantee loop-freedom. DIV generalizes previous loop-free algorithms and provably outperforms them by reducing synchronous updates and helping maintain paths during network changes. The document also reviews link-state routing, distance-vector routing, and existing loop-prevention techniques like the Diffusing Update Algorithm and Loop Free Invariance algorithms.
This document summarizes a study that investigated the formulation of neem seed oil and jatropha seed oil with antimony dialkyldithiocarbohate (ADTC) additives for use as bio-based lubricants. Tribological tests were conducted using a four-ball tribometer to evaluate the lubricity performance of the two oil formulations. The results showed that the jatropha seed oil formulation had lower friction coefficients and better wear protection under the test conditions, indicating it performed better as a lubricant. The study concluded that jatropha seed oil with ADTC additives showed potential for use as an environmentally-friendly bio-based lubricant.
Academic Libraries: Engine Breed Spuring Innovation for Competitiveness and S...IOSR Journals
Abstract: The research was designed to unveil out how academic libraries have assisted institutions in bring up candidates to work in industrial capabilities towards the achievement of competitiveness and sustainable economic growth in society. This study was drawn from the extensive literature review and case studies to discuss the following economic value of accessing information using the library; innovation and services in academic libraries; initiatives, resources and activities that facilitate access to information in the library; FUTO Library and library responding to academic programmes. The following research questions helped ascertain what has made the academic libraries tick in this direction and to find answers to them; what status of people does the library have? To what extent material resources is provided and used by the library patrons? What ICT services are been offered by the library and of what purpose are they offered? What strategy development implied by the library to meet patron’s needs? What are the obstacles the library may encounter in the process to achieve competitiveness and sustainability to serve library patrons? Frequency and percentages were deployed for the study due is within the study environment area. Collection of Data was through the use of questionnaire developed by the researchers. Ninety-five copies of the questionnaires were distributed to staff of FUTO Library, out of which 85 were returned and found useful. Finding was analyzed and results ascertained. Keyword: Library, growth, process, ICT, resources, services, innovation
A six-stroke engine provides two power strokes in each cycle, improving efficiency over a traditional four-stroke engine. It works by using the heat from the exhaust stroke to generate a secondary expansion and power stroke. The first four strokes are identical to a four-stroke engine. In the fifth stroke, water is injected into the hot combustion chamber and turns to steam, expanding to drive the piston down for a second power stroke. This recovers waste heat from the exhaust to improve fuel efficiency over a four-stroke engine by up to 30-40%. However, additional systems are required to inject water and utilize the secondary expansion, increasing complexity over a traditional design.
Effect of substrate temperature on the morphological and optical properties o...IOSR Journals
The document summarizes research on the effect of substrate temperature on the morphological and optical properties of ZnO thin films formed by DC magnetron sputtering. ZnO films were deposited on glass substrates held at temperatures between 473-673 K. Atomic force microscopy analysis showed that substrate temperature affected the roughness and grain size of the films. Optical analysis found that substrate temperature influenced the transmittance, band gap, and extinction coefficient of the films. The films deposited near 513 K exhibited optimal optical properties such as highest transmittance and band gap.
Simulation of a linear oscillating tubular motorIOSR Journals
This document simulates a linear oscillating tubular motor (LOTM) using mathematical equations and computer tools. It begins by describing the components and operating principle of the LOTM, which consists of an iron bar moving inside a coil. The displacement of the iron bar causes periodic variations in the coil inductance.
The document then presents the mathematical equations that govern the LOTM's operation in terms of inductance as a function of displacement. A block diagram shows how these electrical and mechanical equations are solved using simulation. Graphical results from the simulation show how parameters like inductance, magnetic force, and speed vary over time and displacement. In conclusion, the document discusses how further optimization of the LOTM's magnetic circuit and
Control strategies of_different_hybrid_energy_storage_systems_for_electric_ve...PrafulYadav4
This document summarizes control strategies for different hybrid energy storage systems used in electric vehicles. It classifies strategies into four configurations: fuel cell-battery, battery-ultracapacitor, fuel cell-ultracapacitor, and battery-fuel cell-ultracapacitor. The document provides a comparative analysis of control techniques based on aspects like control parameters, vehicle operation, and performance metrics. It also analyzes experimental setups, driving cycle improvements, and mathematical models to demonstrate the reliability of applying these strategies in practice.
The document summarizes a seminar presentation on machine learning. It includes an introduction to machine learning, common machine learning algorithms, and the general machine learning process. It also discusses different types of learning approaches such as supervised, unsupervised, reinforced, and semi-supervised learning. Literature on applications of machine learning in various domains like healthcare, robotics, and power systems is also reviewed.
Application and evaluation of the neural network in gearboxTELKOMNIKA JOURNAL
We developed old designed of a Back-Propagation neural network (BPNN), which it was designed by other researchers, and we made modification in their structure. The 1st velocity ratio was discriminated by lowest speed, and highest twist. The 6th velocity ratio was discriminated by highest speed, and lowest twist. The aim of this paper is to design neural structure get best performance to control an electrical automotive transportation six-speed gearbox of the vehicle. We focus on the evaluation of the BPNN to select the suitable number of layers and neurons. Experimentally, the structure of the proposed BPNN are constructed from four layers: eight input nodes in the first layer that received data in binary number, 45 neurons in 1st hidden-layer, 25 neurons in 2nd hidden-layer, and 6 neurons in the fourth layer. The MSE and number of Epochs are the main factors used for the evaluation of the proposed structure, and compared with the other structures which was designed by other researchers. Experimentally, we discovered that the best value of Epoch and MSE was chosen when the BPNN consisted of two hidden-layers, 45, and 25 neurons in the 1st and 2nd hidden-layer respectively. The implementation was applied using MATLAB software.
Data Driven Energy Economy Prediction for Electric City Buses Using Machine L...Shakas Technologies
Data Driven Energy Economy Prediction for Electric City Buses Using Machine Learning.
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This research proposal aims to optimize kinetic energy recovery systems (KERS) for passenger cars and urban buses through improving the design of power split continuously variable transmissions (CVTs). The research will involve 4 phases: 1) simulating vehicle dynamics to determine KERS constraints, 2) developing a model to predict CVT performance, 3) formulating and solving an optimization problem considering energy savings, costs and size, 4) applying the optimized CVT design to KERS for cars and buses. The goal is to balance factors like ratio spread, efficiency, costs and size to maximize energy recovery during braking.
This document summarizes a research paper on simulating a hybrid electric vehicle powertrain. The paper models a Toyota Prius II, which uses a serial/parallel powertrain configuration with two electric motors and an internal combustion engine. It describes the electrical, mechanical, and energy management subsystems that were modeled. Simulation results showed the model accurately captured power flows and could be used to develop efficient energy management systems.
Effects of Degree of Hybridization and Vehicle Driving Cycle on the Performan...IRJET Journal
This document discusses a study that uses simulation software to analyze the performance of a fuel cell-battery hybrid electric vehicle under different configurations. The study varies the degree of hybridization (the ratio of battery power to total vehicle power) for a 2021 Toyota Mirai fuel cell vehicle model. It finds that increasing the degree of hybridization to 68.7% improves fuel economy by 16.3% compared to the original vehicle specifications. The best-performing configuration is then tested under different driving cycles to evaluate performance under various driving conditions.
Shared Steering Control between a Driver and an Automation: Stability in the ...paperpublications3
Abstract: Now-a-days the Automatic control has been increasingly implemented for vehicle control system. Especially the steering control is essential for preventing accidents. In the existing systems there is no fully automatic steering control and it has serious problems. When it is made automatic, the system complexity is more. So, the shared steering concept is used in the proposed system to avoid accidents. In this, the position of the road is found using the web camera installed in front of the vehicle which is connected to the PC installed with MATLAB. Using MATLAB the image is processed to check the road characteristics. This paper presents an advanced driver assistance system (ADAS) for lane keeping, together with an analysis of its performance and stability with respect to variations in driver behavior. The automotive ADAS proposed is designed to share control of the steering wheel with the driver in the best possible way. Its development was derived from an H2-Preview optimization control problem, which is based on a global driver–vehicle–road (DVR) system. The DVR model makes use of a cybernetic driver model to take into account any driver–vehicle interactions. Such a formulation allows 1) Considering driver assistance cooperation criteria in the control synthesis, 2) improving the performance of the assistance as a cooperative copilot, and 3) analyzing the stability of the whole system in the presence of driver model uncertainty. The developed assistance system improved lane-keeping performance and reduced the risk of a lane departure accident. Good results were obtained using several criteria for human–machine cooperation. Poor stability situations were successfully avoided due to the robustness of the whole system, in spite of a large range of driver model uncertainty.
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
This document summarizes a research paper that uses genetic algorithms to optimize traffic light timing at intersections to minimize traffic. It first describes modeling traffic light intersections using Petri nets. It then explains how genetic algorithms can be used for optimization by coding the problem variables in chromosomes, defining a fitness function to evaluate populations over generations, and using operators like mutation and crossover. The fitness function aims to minimize average traffic light cycle times based on 14 parameters related to light timing and vehicle wait times at two intersections. The genetic algorithm optimization of traffic light timing parameters is found to improve traffic flow at intersections.
The document compares three electric vehicle drivetrain architectures (hub motors, on-board motors, and axle motors) from a vehicle dynamics perspective using MATLAB simulations. For anti-lock braking system simulations, different control strategies are used to blend electric motor torque with hydraulic brake torque. Optimal slip-tracking control improves stopping distance the most compared to other strategies for all architectures. For vehicle stability control simulations, on-board and hub motor architectures require higher wheel torque due to higher effective wheel inertia, causing higher tire slip. Optimal slip-tracking control reduces tire slip and vehicle sideslip angle by specifying optimal reference slip values. Tire slip trends are lower with hub motors due to more precise slip control.
The energy consumption of electric vehicles (EVs)depends on traffic environment, terrain, resistive forces acting on vehicle, vehicle characteristics and driving habits of driver. The battery pack in EV is the main energy storage element and the energy capacity determines the range of vehicle. This paper discusses the behavior of battery when EV is subjected to different driving environments such as urban and highway. The battery rating is selected based on requirement of driving cycle. The MATLAB/Simulink model of battery energy storage system (BESS) consisting of battery, bidirectional DC/DCconverter and electric propulsion system is built. The simulation is carried out and the performance of BESS is tested for standard driving cycles which emulate actual driving situations. It has been shown that, the amount of the energy recovered by battery during deceleration depends on the amount of regenerative energy available in the driving cycle. If the battery recovers more energy during deceleration, the effective energy consumed by it reduces and the range of the vehicle increases.
Model Validation and Control of an In-Wheel DC Motor Prototype for Hybrid El...Scientific Review SR
In this paper, a mathematical model and a controller for a DC motor are developed for the
construction of an in-wheel motor. In-wheel motors can be used in hybrid electric vehicles to provide traction
force of front or rear wheels. The model identification is achieved using a simple and low cost data acquisition
system. An Arduino Uno embedded board system is used to collect data from sensors to a computer and for
control purposes. Data processing is performed using Matlab/Simulink. Validations of the devel oped
mathematical model and controller performance are carried out by comparing simulation and experimental results.
The results obtained show that the mathematical model is accurate enough to assist in speed controller design and
implementation.
IRJET- Regenerative System and it’s ApplicationIRJET Journal
This document discusses regenerative braking systems. It begins with an abstract that introduces regenerative braking as a system that can recapture kinetic energy during braking and convert it to electrical energy. It then provides background on regenerative braking and how it works. The document reviews several past studies on regenerative braking systems and their applications in electric vehicles. It discusses the components and working of a regenerative braking system, including how kinetic energy is captured during braking by a flywheel and generator and stored in a battery.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered as the main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance, which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Investigation of Ant Colony Optimization Algorithm for Efficient Energy Utili...IJCNCJournal
Maintaining the energy conservation is considered as an important approach to increase the lifetime of WSN. In fact, an energy reduction mechanism is considered asthe main concept to enhance the lifespan of the network. In this paper, the performance analysis/evaluation of optimization technique, specifically, Ant Colony Optimization (ACO) and modified ACO (m-ACO) in the routing method are investigated. This network analysis is done by 100 iterations and differentiated with 50, 75 and 100 numbers of nodes. Finally, experimental results illustrate that the performance of m-ACO algorithm obtained the obvious performance,which is comparatively better than ACO algorithm, because it improves the routing efficiency by pheromone evaporation control and energy threshold value. It demonstrates that m-ACO algorithm gives better results than ACO in terms of throughput (1.41%), transmission delay (1.43%), packet delivery ratio (1.41%), energy consumption (2.05%), and the packet loss (9.70%). The convergence rate is analysed for ACO and m-ACO algorithms with respect to 100 number of iterations for WSNs.
Deep neural network for lateral control of self-driving cars in urban environ...IAESIJAI
The exponential growth of the automotive industry clearly indicates that self-driving cars are the future of transportation. However, their biggest challenge lies in lateral control, particularly in urban bottlenecking environments, where disturbances and obstacles are abundant. In these situations, the ego vehicle has to follow its own trajectory while rapidly correcting deviation errors without colliding with other nearby vehicles. Various research efforts have focused on developing lateral control approaches, but these methods remain limited in terms of response speed and control accuracy. This paper presents a control strategy using a deep neural network (DNN) controller to effectively keep the car on the centerline of its trajectory and adapt to disturbances arising from deviations or trajectory curvature. The controller focuses on minimizing deviation errors. The Matlab/Simulink software is used for designing and training the DNN. Finally, simulation results confirm that the suggested controller has several advantages in terms of precision, with lateral deviation remaining below 0.65 meters, and rapidity, with a response time of 0.7 seconds, compared to traditional controllers in solving lateral control.
Two-way Load Flow Analysis using Newton-Raphson and Neural Network MethodsIRJET Journal
The document presents a study comparing two-way load flow analysis using the Newton-Raphson method and a neural network method for networked microgrids. The optimal power flow problem is solved using both a conventional Newton-Raphson method and an artificial intelligence neural network method. Results show that the neural network method achieves minimum losses and higher efficiency compared to the Newton-Raphson method, with efficiencies of 99.3% and 97% respectively for the test networked microgrid system.
DESIGN & DEVELOPMENT OF MECHANICAL VARIABLE TRANSMISSION SYSTEM WITH HIGH STA...IRJET Journal
The document discusses several studies and designs related to electric vehicles. It begins by summarizing a study that designed a mechanical variable transmission system for electric vehicles to achieve high starting torque and speed. Several other studies are then summarized that evaluate factors for sustainable electric vehicle manufacturing in India, analyze the performance of low-speed electric two-wheelers in urban traffic, mathematically model electric vehicles, design hybrid electric bikes and transmission systems, extract requirements for designing electric two-wheelers, propose petro-electric bike designs, review motor selection for electric vehicles, discuss the design of electric superbike racing vehicles, compare energy consumption and costs of electric vehicle transmissions, propose a design for a next generation electric bike, and provide biographies of the
Design and analysis of a new brake-by-wire system using machine learning IJECEIAES
This document proposes a new brake-by-wire system that replaces the brake pedal with pressure sensors embedded in the steering wheel. It discusses the design of the pressure braking batch sensors, which would translate pressure on the wheel to an electrical signal and braking force. The document also addresses the challenge that different people have different muscle strengths, so it cannot be assumed that a certain pressure always corresponds to the same braking intention. To address this, the document proposes collecting a dataset from volunteers pressing the sensors at different strengths to train a machine learning model to classify the intended braking level from the sensor readings. Preliminary results show that a regression tree algorithm achieved the best performance in predicting the braking class from the volunteer data.
Driving cycle is commonly known as the relationship and a series of speed-time profile. The study on this discipline aids vehicle manufacturers in vehicle construction, environmentalists in studying environment quality in proportion with vehicle emissions and traffic engineers to further investigate the behaviour of drivers and the road conditions which assist automotive industry in a better and energy efficient vehicle productions. In order to develop a proper driving cycle for selected routes, information and data based on real-time driving behaviour is important. This research focusses on the modelling of each component and latter designing a conceptual model in Simulink which takes up the data of speed of vehicles in SI unit which is m/s and draws out distance travelled and acceleration of the vehicle together with driving cycle of the route for given timestamp. This relation will be verified with existing Kuala Terengganu BasKITe driving cycle, highway fuel economy test (HWFET), new europian driving cycle (NEDC) and worldwide harmonised light vehicle test procedure (WLTP) driving cycles for the use of future projects and improvements of technology in studies and analysis of powertrain and electric vehicle performances.
This document provides a technical review of secure banking using RSA and AES encryption methodologies. It discusses how RSA and AES are commonly used encryption standards for secure data transmission between ATMs and bank servers. The document first provides background on ATM security measures and risks of attacks. It then reviews related work analyzing encryption techniques. The document proposes using a one-time password in addition to a PIN for ATM authentication. It concludes that implementing encryption standards like RSA and AES can make transactions more secure and build trust in online banking.
This document analyzes the performance of various modulation schemes for achieving energy efficient communication over fading channels in wireless sensor networks. It finds that for long transmission distances, low-order modulations like BPSK are optimal due to their lower SNR requirements. However, as transmission distance decreases, higher-order modulations like 16-QAM and 64-QAM become more optimal since they can transmit more bits per symbol, outweighing their higher SNR needs. Simulations show lifetime extensions up to 550% are possible in short-range networks by using higher-order modulations instead of just BPSK. The optimal modulation depends on transmission distance and balancing the energy used by electronic components versus power amplifiers.
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1. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE)
e-ISSN: 2278-1684,p-ISSN: 2320-334X, Volume 13, Issue 1 Ver. V(Jan. - Feb. 2016), PP 31-40
www.iosrjournals.org
DOI: 10.9790/1684-13153140 www.iosrjournals.org 31 | Page
ANN based intelligent energy management control of hybrid
vehicle for improving fuel consumption
Zoonubiya Ali1
, Dr.S.L Badjate2,
Dr.R.V.Kshirsagar3
1
(Electronics & Telecommunication Engineering, Disha Institute of Management and
Technology/CSVTU,India)
2
(Electronics & Telecommunication, S.B Jain Institute of Technology management & Research/ N.U, India)
3
(Electronics Engineering, Priyadarshini college of Engineering/ N.U, India)
Abstract:Every passing year hybrid electric vehicles are becoming popular. After so much improved result it
seems to be one of the potential solutions of global problems like global warming, rise in fuel prices, pollution
etc. Due to various non linear parameters which are included in developing hybrid electric vehicles many a time
to develop and achieve this new emerging technology, its analytical procedure is time consuming and it requires
simplifying assumption. One practical alternative to analytical and empirical method that is easy and more
accurate is Artificial Neural Network (ANN). For modeling complex real world problem in many discipline,
Artificial Neural Network have emerged as computational modeling tool. To reduce fuel consumption and
emission problems environmental condition, driver’s behavior and types of roadway were considered very
influential. So to analyze the vehicle’s performance all these factors are incorporate in the system and presented
in this paper. Artificial environmental data for elaborating vehicles performance is created artificially by neural
network. Model for road way, SOC, vehicle, driver behavior and environment condition were created and ANN
is being developed for all models.
Key words: Artificial neural network (ANN), fuzzy logic, fuel consumption, hybrid vehicle.
I. INTRODUCTION
As compared to normal gasoline vehicle, a hybrid vehicle gives less fuel consumption and carbon
emissions. Control strategy is the main key objective which is to be held responsible for achieving the improved
performance and success of hybrid vehicle. Control strategy oh hybrid vehicle is broadly divided in two types
rule based strategy and optimal control strategy for both series and parallel vehicles. Various researchers are
using rule based control which is based on human expertise, mathematical and heuristic information. Rules
based are again categorized in three different types; rule based which uses human knowledge for writing rules.
Fuzzy logic based, which have more robust structure and can provide flexibility to controller because of non
linear structure and can easily deal with non linear problem of power splitting between two sources of
controller. The last type of rule based control strategy isNeuro-fuzzy which is the combination of fuzzy logic
and artificial neuro-fuzzy control.
FIGURE 1: OPTIMAL CONTROL STRATEGY
Whereas the Optimal control strategy is another category which is further subdivides into global
optimization (offline) and real time optimization (online) type. The optimal strategy is perfect and the controller
is optimized according to cost function of system. But these controllers are sensitive to noise. Here both static
and dynamic behaviors have to be taken into consideration for achieving optimized results.
Various researches have been carried out by combining various categories stated above for series as
well as for parallel. ANFIS (adaptive neuro-fuzzy inference system) integrate the best features of fuzzy logic
and neural network and so it has attracted the interest of researchers to synthesis controllers and to develop the
2. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 32 | Page
models to explain past data and predict future behavior. ANFIS based online SOC (State of Charge) correction
considering cell divergence for the EV (electric vehicle) traction batteries is developed [Haifeng Dai et al.
(2014)].
Recent developments in artificial neural network (ANN) control technology have made it possible to
train an ANN to represent a variety of complicated nonlinear systems [B. K. Bose (2007)]. ANN is a simulation
of the human brain and nervous system built of artificial neurons and their interconnections. The ANN can be
trained to solve the most complex nonlinear problems with variable parameters similar to the human brain. A
neural network is an interconnected assembly of simple p rocessing elements, units or nodes, whose functionality
is loosely based on the neuron. The processing ability of the network is stored in the inter-unit connection
strengths, or weights, obtained by a process of adaptation to, or learning from, a set of training patterns. The
attractive feature of ANN is its
Non linearity,
High parallelism,
Fault and noise tolerance
Learning capabilities
II. VARIOUS ANN MODEL FOR HYBRID VEHICLES
Real time control strategy based of Elman neural network for the parallel hybrid electric vehicle is used
by [Ruijun Liu et al. (2014)], their work discuss about equivalent fuel consumption function under charging and
discharging conditions of batteries. The instantaneous control strategy and Elman neural network were
simulated and analyzed in ADVISOR. Results prove 96% reduce simulation time and improve the real time
performance of controller in addition with good performance of power and fuel economy.
In another work modeling, analysis, and simulation of an electric vehicle (EV) with two independent
rear wheel drives were done. Generalized neural network algorithm proposed to estimate the vehicle speed.
Neural network traction control approaches of an electrical differential system for an Electric vehicle (EV)
propelled by two induction motor drives were stated. A practical speed estimation method for an induction
motor was proposed where a recurrent neural network (RNN) with two hidden layers were used. RNN used
called the Elman neural network. This algorithm were used to improve EV steering and stability during
trajectory changes
Multi-Perceptron Neural Network were trained using Resilient Back Propagation algorithm to predict
the suitable mode among between only motor modes, only engine mode, engine plus motor mode, charging
mode and regenerative mode. The network trained to an error of 0.005 in 1300 iterat ions. After predictions of
mode were done, the battery SOC (state of charge) was calculated. For energy optimization of hybrid algorithm
shows 17.4% improvement in fuel consumption results. This hybrid algorithm can be used for both on line and
online.
S.R. Bhatikar (1999) demonstrates the work energy storage system modeling based on neural network.
The model maps the system’s state-of-charge (SOC) and the vehicle’s power requirement to the bus voltage and
current. Work proposes and deploys new technique, smart select for designing neural network training data.
When validated its predictive accuracy, measured by R-squared error was 0.97. The energy storage model using
neural network simulated in Matlab environment. The results of simulation with the ANN incorporated in
ADVISOR shows the matching with the original ADVISOR algorithm.
In one approach a neural network based trip model for highway portion was explained by [Qiuming
Gong (2009)]. 3 inputs, 2 outputs network was developed for the fitting of the driving pattern on highway near
on/off ramps. The trained neural network can obtain a good fitting of the driving pattern. The simplified
approach makes the trip model on highway much easier. The interpolation model with NN is used and the fuel
economy is greatly improved. The NN model presents a simplified and effective way for this detailed model of
trip model considering the on/off ramp flows.
A new energy management system is proposed [Hamid Khayyam et al. (2014)] to improve the vehicle
efficiency using a backwards-forwards simulation similar to the technique employed by ADVISOR [Khayyam
H et al.(2011)],[Wipke KB et al. (1999)]. Models of vehicle engine, air conditioning, power train, and hybrid
electric drive system were developed in addition with model for Road geometry and thermal conditions. Due to
the nonlinear and complex nature of the interactions between parallel hybrid electric vehicles
(PHEV),environment driver components, a soft computing based intelligent management system were
developed using different fuzzy logic controllers. Applying a hybrid multi-layer adaptive neuro-fuzzy inference
systemand then optimized using genetic algorithm is capable of improving the fuel efficiency of the vehicle.
3. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 33 | Page
III. ARCHITECTURE OF ANNBASED APPROACH
FIGURE 2: ARCHITECTURE OF ARTIFICIAL NEURAL NETWORK
To improve energy management strategy and to optimize the performance and efficiency of hybrid
electric vehicle, modeling and simulation has become a very important approach for researchers. It also helps to
reduce vehicle development time to larger extent and to optimize vehicle system design. Modeling and
simulation helps in achieving insight into the functionality of the modeled vehicle systems and in investigating
the systems behaviors and performance. To reduce fuel consumption and emission problem environmental
condition, driver’s behavior and types of roadway were considered very influential [11]. So to analyze the
vehicle’s performance all these factors should be incorporate in the system. To incorporate role of environment,
roadway type and drivers style in simulation environment either real or artificial data is to be needed. But it is
difficult many a time to use real or inadequate for extensive data for simulations. So artificial environmental
data for, elaborating vehicles performance was created artificially by neural network using different models. The
artificial data which was created poses the entire characteristic those of the real data for modeling and
simulations. Model for road way, driver behavior and environment condition were created and ANN is
developed for all models. To properly inspect the role of environment conditions in modeling and simulation
two types of environment condition were used. One for road geometry and another for wind condition, that talks
about weather condition. Real environment data many a time may not provide enough information therefore
simulations are performed under control environmental condition. Comprehensive set of artificial data were
created by different distribution in neural network [Khayyamet al (2013)]. Enormous slopes and bends exist in
real world [13]. When roads are designed numerous geometric design methods could be used to smooth its
physical slopes and bends. Carefully designed roads can help to optimize the performance of vehicle. A road has
been constructed using a collection of segments. Xyz collected using sensor UDP i.e. application of android
phone. Then based open the information collected from the sensor the segment length, bend, slope alt itude
direction all these parameters were decided. For this purpose equations stated by [Hamid Khayyam (2013)]were
utilized and using these input and output data, ANN were trained. The roadway type LOS A, LOS B, LOS
C,LOS D,LOS E and LOS F were generated at output with same concepts that were used by author to develop
using ANFIS. Based on this training of ANN for road geometry was done. Similarly in order to model wind
condition, region length, region type, and wind speed and wind direction were consider. Wind is highly
metrological element both in speed and direction. And data regarding this were generated using various
distributions. This data is again in term of 1, 45,000 units and this will helped to find out the drag force which
the resistance coming from the wind. Then the model for driver’s behavior was considered to generate driver’s
style at the output of ANN model. The concepts of ANFIS were used for generating calm, normal and
aggressive style of driver. Average acceleration and standard deviation were generated by randomvariable ANN
based modeling. Using all this information, vehicle speed, road power demand, torque at crank shaft (wheel)
4. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 34 | Page
and crank shaft speed an artificial neural network for vehicle was designed which is going to give gear ratio and
in term it is going to find out the power consumption and fuel consumption[Hamid Kayyam (2013),(2010)].
In order to know the state of charge of battery when it is cruising or moving, battery model fitted to
Honda insight has been used. An ANN for battery has been generated by considering battery voltage, battery
power demand, battery internal resistance and charge capacity of battery. Equations have been used to compute
state of charge of battery. This state of charge decide the propulsion of vehicle and control strategy is only to
make SOC as high as possible so that maximum propulsion would takes place by battery to achieve maximum
fuel efficiency and also to reduce emission ,which is the prime objective of this work.
Depending on this gear ratio and state of charge of battery, an ANN has been developed for selecting
power for hybrid vehicle. The decision was based on selecting battery or internal combustion engine. Fuel
efficiency map unit was also used to compare the result..
1.1 ANN FOR ROAD WAY TYPE
An ANN for road geometry has been developed by considering segment length, Bend, slope of the road
and altitude direction of specific road. A road has been constructed using a collection of segments. Xyz
collected using sensor UDP i.e. application of android phone. Total 1, 45,000 positions were recorded. Then
based open the information collected from the sensor the segment length, bend, slope altitude direction all these
things were decided and ANN was trained. The roadway type LOS A, LOS B, LOS C, LOS D, LOS E and LOS
F were generated at output with same concepts that have already been used for ANFIS by author.
Using the available Cartesian coordinates, the altitude (ALT), direction (DIR), and slope angle (Slope)
of the road can be calculated as follows:
𝐴𝐿𝑇 = 𝑧 (1)
𝐷𝐼𝑅 =
180𝑋 𝑎𝑟𝑐 𝑡𝑎𝑛𝑔𝑒𝑡
𝑑𝑥
𝑑𝑦
𝜋
(2)
𝐷 = 𝑥2 + 𝑦2 + 𝑧2 (3)
Slope=
𝑑𝑧
𝑑𝑦
(4)
The random numbers for height and bend could be small or large for varying degree of height and
bends into different road segment. The data bases were generated by using above equations for altitude (1),
direction (2), distance (3) and slope (4). Using this data base roadway type was decided.
FIGURE 3: ANN MODEL FOR ROAD GEOMETRY
1.2 ANN FOR WIND
The empirical distributions of real wind direction data could not be well fitted by any form of standard
distributions. One very simple approach was applied by considering uniform distribution upon an interval with
the minimum and maximum values respectively. Speed and direction are the two parameters which have been
consider for future simulation. A wind is constructed using a collection of regions of differing lengths. A wind
creation algorithm is an iterative routine. The algorithm creates wind speed and direction values for each region.
Random numbers were used to generate region length, wind speed value in the region, and also for wind
direction in the region.
In order to model wind condition –we have consider region length ,region type , wind speed and wind
direction and data regarding this were generated using various distribution from proper references . This data is
again in term of 1, 45,000 units and this is utilized to find out the drag force which is the resistance coming from
Segment length
ANN for
RoadGeometry
Bend of Road
Slope of Road
Altitude
Direction
Roadway Type
(LOS A – LOS F)
5. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 35 | Page
the wind. The equation which was used to calculate this drag force is shown below.
𝑓𝑜𝑟𝑐𝑒 = 𝐶 𝑑𝑟𝑎𝑔 (𝛷)
1
2
𝜌(𝑉𝜔 + 𝑉𝑡 )2 𝐴 𝛷 𝑉𝑡 − 𝑚 𝑔 sin 𝛳 𝑣𝑡 (5)
Wherecdraq is draq coefficient, ρ- air density, A-front area, Vω —wind velocity, Φ-wind angle
FIGURE 4: ANNMODEL FOR WIND
1.3 ANN FOR DRIVER BEHAVIOR
[De- Velieger et al. (2000)] stated three different style or behavior of driver by comparing on how they
are using acceleration — Calm driving, normal driving and aggressive driving.
FIGURE 5: ANN FOR DRIVER BEHAVIOR.
Driver with calm driving follows all the traffic rules and avoid all the hurdles of road very calmly by
avoiding hard acceleration and instant braking during driving. For normal driving driver uses moderate
acceleration and normal braking. And for aggressive driving driver uses sudden acceleration hard braking and
sudden gear change. Emissions and fuel consumption obtained fromaggressive driving is always high compared
to normal and calm driving. Average acceleration and Standard Deviation (SD) of acceleration over a specific
driving range were used to identify the driving style. Acceleration criteria for the classification of the driver’s
style are based on the acceleration ranges proposed here. Average acceleration is considered from 0 to 0.9207
and standard deviation of acceleration is 0 to 0.8. Model for ANN were developed by using average
acceleration and standard deviation. Data base for both were generated by using random function in neural
network environment. Neural network was trained by using the data base generated. Depending upon the ranges
specified network observes at output style of driver, i.e. calm, normal and aggressive. All three ANN of
Roadway type, ANN of wind and ANN for driver behavior were club together and road power demand were
created and it is used for developing ANN for vehicle[15][12].
1.4 ANN FOR VEHICLE:
In parallel hybrid electric vehicle, internal combustion engine and battery gives power to vehicle. A
model for vehicle was developed using ANN to achieve proper gear ratio. Vehicle speed , road power demand ,
torque at crank shaft(wheel) and crank shaft speed were used by an artificial neural network for vehicle and was
designed which is going to provide proper gear ratio and in term it is going to find out the power consumption
and fuel consumption. For this particular thing we are using the flowing equation referred from references.
Region length
Region Type
Wind Speed
Wind Direction
ANN for Wind Force (Cdrag)
Average Acceleration
Standard Deviation
ANN for Driver
Behavior
Style of Driving
Calm, Normal,
Aggressive
6. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 36 | Page
FIGURE 6: ANN FOR VEHICLE
𝑃𝑅𝑃𝐷(𝑐𝑟𝑜𝑙𝑙𝑖𝑛𝑔 ) = 𝑚 𝑔 cos 𝛳 𝑉𝑡 + 𝐶 𝑑𝑟𝑎𝑞
1
2
𝜌(𝑉𝜔 + 𝑉𝑡 )2 𝐴 𝛷 𝑉𝑡 − 𝑚 𝑔 sin 𝛳 𝑉𝑡 (6)
Ƶ 𝑑 =
𝜔 𝑟
𝑑 𝑟
1
𝑔 𝑟(𝑡)
𝑃 𝑅𝑃𝐷
𝑉(𝑡)
(7)
𝜔(𝑡) =
𝑑 𝑟
𝜔 𝑟
𝑔 𝑟(𝑡) 𝑉(𝑡) (8)
𝜔(𝑡)is crank shaft speed ,𝑑 𝑟 is differential ratio , 𝑔 𝑟(𝑡) is selected gear ratio and 𝑉(𝑡)is vehicle speed.
𝑇𝑄(𝑊𝑒𝑒𝑙𝑠 ) = 𝑇𝑄(𝑒𝑛𝑔𝑖𝑛𝑒 ) 𝑋𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑟𝑎𝑡𝑖𝑜 𝑓𝑜𝑟 𝑐𝑜𝑠𝑒𝑛 𝑔𝑒𝑎𝑟𝑋𝐴𝑥𝑙𝑒 𝑟𝑎𝑡𝑖𝑜 (9)
𝑆𝑝𝑒𝑒𝑑 𝑉𝑒𝑖𝑐𝑙𝑒 =
𝑒𝑛𝑔𝑖𝑛𝑒 𝑅𝑃𝑀 𝑥 𝑇𝑖𝑟𝑒 𝑅𝑎𝑑𝑖𝑢𝑠 𝑥2𝜋
𝑇𝑟𝑎𝑛𝑠𝑚𝑖𝑠𝑠𝑖𝑜𝑛 𝑟𝑎𝑡𝑖𝑜 𝑥 𝐴𝑥𝑙𝑒 𝑟𝑎 𝑡𝑖𝑜 𝑓𝑜𝑟 𝑐𝑜𝑠𝑒𝑛 𝑔𝑒𝑎𝑟
(10)
𝑃𝑜𝑤𝑒𝑟 𝑤𝑒𝑒𝑙 = 𝑃𝑜𝑤𝑒𝑟 𝑒𝑛𝑔𝑖𝑛𝑒− 𝑃𝑜𝑤𝑒𝑟 𝑙𝑜𝑠𝑠𝑒𝑠 (11)
1.5 ANN FOR STATEOFCHARGEOF BATTERY:
Now in order to know the state of charge of that particular battery when it is cruising or it moving ,we
have consider the battery model which is fitted to Honda insight and following are the parameters of the battery.
In order to compute state of charge few equations stated below have been used for developing ANN for battery.
In order to improve the overall efficiency it is necessary to indicate the actual charging level of the battery, the
State of Charge (SOC) is often used [16]. However, the physical background of SOC has a strong relation with
battery models based on current and voltage. The specification of battery used is as follows:
Table: 1 Specification of Battery
S. NO PARAMETERS SPECIFICATION
1 Lithium Ion 12v nominal voltage
2 Nominal capacity 26.2 AH
3 Number of cells in series 07
4 Number of modules in parallel 2
5 Back energy capacity 9.7kwH
6 Minimum voltage 9.5
7 Maximum voltage 16.5v
8 Internal resistance 0.05Ω
Vehicle
Speed
Road Power
Demand
Torque at
crank shaft
Crank shaft
speed
ANN Controller for
Vehicle
Gear Ratio
7. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 37 | Page
Figure 7: ANN model for battery SOC
Battery internal resistance( R) , open circuit voltage(voc), battery power demand (Pbat)and battery
charge capacity(Q) are input parameters which allow for output voltage to be calculated based on battery state of
charge (SOC).
Battery power availability information for charging and discharging is transmitted to the vehicle
controller as well as to the electric drive components for propulsion and to accessories for miscellaneous use.
An ANN has been developed for battery state of charge (SOC). Four inputs of battery internal resistance, open
circuit voltage, and battery power demand and battery capacity were considered as input for developing this
ANN. The following is the equation used to generate SOC as output of ANN.
𝑆𝑂𝐶 =
𝑉𝑂𝐶 𝑠𝑜𝑐 − 𝑉𝑂𝐶 𝑠𝑜𝑐 2−4𝑃𝑏𝑎𝑡𝑡𝑒𝑟𝑦𝑅
2𝑄𝑅
(12)
Here in ANN VOC is taken between range 9.5 to 16.5V and it is generated by random distribution
method. Battery power demand is from 0 to 9.7kwh which also generated by random distribution method.
Battery internal resistance and battery charge are kept constant with a value of 0.05Ω and 26.2Ah. Using the
data base generated proper value of SOC can be calculated to decide the power for propulsion by ANN. Using
this state of charge value and proper gear ratio the algorithm for selecting power source is applied, which
actually decide the power selection between internal combustion engine and battery. Fuel efficiency map unit
plays a very major role of comparing the result obtained to make decision between two power sources. In PHEV
one of the primary goals is to set the engine operation in its peak efficiency region. This improves the overall
efficiency of the power train. The ICE operation is set according to the road load and the battery state of charge
(SOC).
IV. SIMULATION RESULT
For this study advisor as reference software were considered. This is the customized software for
parallel vehicle and Honda insight vehicle is available for in this particular software. Considering it is a
reference for one particular cycle of 1.7 km following results were obtained. Fuel consumption of ANN and
ANFIS matches with the fuel consumption of Advisor.
Figure 8: Fuel consumption curve
1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 2900 3000
0
0.2
0.4
0.6
0.8
1
1.2
x 10
-3
Engine Speed RPM
FuelRate(litre/sec)
Fuel Consumption
galadvisor
galFCEMS
galANNEMS
Battery Open
circuit voltage
Battery Power
Demand
Battery internal
resistance
Battery charge
capacity
Battery State of
charge (SOC)
ANN for battery
(SOC)
8. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 38 | Page
Then power consumption shows similar trend only difference is that it has certain picks which is
moving away from advisor the reason might be probalistic nature of fuzzy logic or anfis or neural network
Figure 9: Power consumption curve
Then these results are about the torque demand and this demand is coming from driver to drive the
vehicle. Fig (9) shows that all 3 plots are properly match.
Figure 9: Torque Curve
The compiled results are shown in Table 2. Trip length considered was 1.7km and duration of travel is
consider 1170 sec and have observed that fuel consumption is around 15% more in case of ANFIS and ANN as
compared to advisor where 4.1 E -04 is average value and 15 is percentage value. The power consumption is
more by 7.2 and 8% in ANFIS and ANN as compared to advisor. The torque demand is slightly more in ANFIS
and ANN. And battery soc needs to rectify this in current it is 10 and 20% more.
Table 2Comparison of ANFIS and ANN based controller performance with ADVISOR
Parameter
Trip
length
Duration
Fuel
Consumption(liter/sec
)
Power
Consumption(watt)
Torque(N-m) Battery SOC(v)
ADVISOR 1.7km 1170sec 3.6E -04 16366 63.05 6.73
ANFIS 1.7km 1170sec 4.1E -04 (15%) 17306(7.26%) 63.61(0.9%) 7.41(10.15%)
ANN 1.7km 1170sec 4.2E-04(15.36%) 17715(8.79%) 63.72(1.07%) 8.1(20.32%)
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 11501170
0
2
4
6
8
10
x 10
4
Time (second)
PowerConsumtion(watt)
Power consumption
power advisor
power FCEMS
power ANNEMS
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 950 1000 1050 1100 11501170
-100
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
60
70
80
90
100
Time
TorqueDemand
Torque Demand
torqueadvisor
torqueFCEMS
torqueANNEMS
Best
9. ANN based intelligent energy management control of hybrid vehicle for improving fuel consumption
DOI: 10.9790/1684-13153140 www.iosrjournals.org 39 | Page
V. Conclusion
ADVISOR software consists of all the specifications of Honda Insight. The default option of parallel
hybrid vehicle was selected. The performance of ANFIS based controller & ANN based controller were
validated with ADVISOR. The error in prediction of performance for ANFIS as well as ANN is between 0-10
percent as compared with ADVISOR. More trip length and variety of trips needs to be considering for proper
validation of proposed methods. The environmental condition does affect the performance of controller and
hence some more conditions need to be considered. Simulations results shows fuel efficiency and emissions
along with power switching pattern is reduced to larger extent.
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